The Mythical Man-Month Essays on Software Engineering, Anniversary Edition.pdf
2019-12-21 20:09:17 14MB The Mythical Man-Month Essays
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斯坦福大学的经典教材,涵盖了数字通信理论的方方面面,是非常好的教材
2019-12-21 20:05:40 15.47MB 斯坦福 数字通信
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Hull, Elizabeth; Jackson, Ken; Dick, Jeremy 国外非常有名的需求工程书籍。
2019-12-21 20:04:08 7.74MB 需求工程 Requirements Engineering
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安全工程 by ross anderson
2019-12-21 19:59:22 5.88MB 安全
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In response to the exponentially increasing need to analyze vast amounts of data, Neural Networks for Applied Sciences and Engineering: From Fundamentals to Complex Pattern Recognition provides scientists with a simple but systematic introduction to neural networks. Beginning with an introductory discussion on the role of neural networks in scientific data analysis, this book provides a solid foundation of basic neural network concepts. It contains an overview of neural network architectures for practical data analysis followed by extensive step-by-step coverage on linear networks, as well as, multi-layer perceptron for nonlinear prediction and classification explaining all stages of processing and model development illustrated through practical examples and case studies. Later chapters present an extensive coverage on Self Organizing Maps for nonlinear data clustering, recurrent networks for linear nonlinear time series forecasting, and other network types suitable for scientific data analysis. With an easy to understand format using extensive graphical illustrations and multidisciplinary scientific context, this book fills the gap in the market for neural networks for multi-dimensional scientific data, and relates neural networks to statistics. Features x Explains neural networks in a multi-disciplinary context x Uses extensive graphical illustrations to explain complex mathematical concepts for quick and easy understanding ? Examines in-depth neural networks for linear and nonlinear prediction, classification, clustering and forecasting x Illustrates all stages of model development and interpretation of results, including data preprocessing, data dimensionality reduction, input selection, model development and validation, model uncertainty assessment, sensitivity analyses on inputs, errors and model parameters Sandhya Samarasinghe obtained her MSc in Mechanical Engineering from Lumumba University in Russia and an MS and PhD in Engineering from Virginia Tech, USA.
2019-12-21 19:55:19 6.77MB 神经网络
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Advanced Engineering Mathematics 9ed 作者: Erwin Kreyszig(part 1) 英文, 最新版! 共两部分, 此为上部 工程数学 9版
2019-12-21 19:51:02 14.2MB Advanced Engineering Mathematics 9ed
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Advanced Engineering Mathematics 9ed 作者: Erwin Kreyszig(part 2) 英文, 最新版! 共两部分, 此为下部 工程数学 9版
2019-12-21 19:51:02 13.69MB Advanced Engineering Mathematics 9ed
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第三版的 轨道力学 英文文字版 PDF 附带 Matlab 代码、 勘误
2019-12-21 19:50:57 15.56MB 轨道力学 第三版 Matlab
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WaSP.Engineering.wasp组件
2019-12-21 19:48:59 17.23MB 微观选址
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机器学习的利器! 特征选择的法宝! kaggle 必备书! -----Shi Long
2019-12-21 19:48:49 13.61MB 特征选择 机器学习 kaggle
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